mlr_measures_classif.mbrier: Multiclass Brier Score

In mlr3: Machine Learning in R - Next Generation

Multiclass Brier Score

Description

Measure to compare true observed labels with predicted probabilities in multiclass classification tasks.

Details

Brier score for multi-class classification problems with k labels defined as

\frac{1}{n} \sum_{i=1}^n \sum_{j=1}^k (I_{ij} - p_{ij})^2.

I_{ij} is 1 if observation x_i has true label j, and 0 otherwise. p_{ij} is the probability that observation x_i belongs to class j.

Note that there also is the more common definition of the Brier score for binary classification problems in bbrier().

Dictionary

This Measure can be instantiated via the dictionary mlr_measures or with the associated sugar function msr():

mlr_measures$get("classif.mbrier")
msr("classif.mbrier")

Parameters

Empty ParamSet

Meta Information

• Type: "classif"

• Range: [0, 2]

• Minimize: TRUE

• Required prediction: prob

Note

The score function calls mlr3measures::mbrier() from package mlr3measures.

If the measure is undefined for the input, NaN is returned. This can be customized by setting the field na_value.

See Also

Dictionary of Measures: mlr_measures

as.data.table(mlr_measures) for a complete table of all (also dynamically created) Measure implementations.

Other classification measures: mlr_measures_classif.acc, mlr_measures_classif.auc, mlr_measures_classif.bacc, mlr_measures_classif.bbrier, mlr_measures_classif.ce, mlr_measures_classif.costs, mlr_measures_classif.dor, mlr_measures_classif.fbeta, mlr_measures_classif.fdr, mlr_measures_classif.fn, mlr_measures_classif.fnr, mlr_measures_classif.fomr, mlr_measures_classif.fp, mlr_measures_classif.fpr, mlr_measures_classif.logloss, mlr_measures_classif.mauc_au1p, mlr_measures_classif.mauc_au1u, mlr_measures_classif.mauc_aunp, mlr_measures_classif.mauc_aunu, mlr_measures_classif.mauc_mu, mlr_measures_classif.mcc, mlr_measures_classif.npv, mlr_measures_classif.ppv, mlr_measures_classif.prauc, mlr_measures_classif.precision, mlr_measures_classif.recall, mlr_measures_classif.sensitivity, mlr_measures_classif.specificity, mlr_measures_classif.tn, mlr_measures_classif.tnr, mlr_measures_classif.tp, mlr_measures_classif.tpr

Other multiclass classification measures: mlr_measures_classif.acc, mlr_measures_classif.bacc, mlr_measures_classif.ce, mlr_measures_classif.costs, mlr_measures_classif.logloss, mlr_measures_classif.mauc_au1p, mlr_measures_classif.mauc_au1u, mlr_measures_classif.mauc_aunp, mlr_measures_classif.mauc_aunu, mlr_measures_classif.mauc_mu, mlr_measures_classif.mcc

mlr3 documentation built on Sept. 24, 2024, 9:07 a.m.